LEARNING OBJECTIVES

After completing this chapter, you should be able to do the following:

•     Recognize how optimization is used with Big Data.

•     Recall an actual example of Big Data in the electronics retail business.

•     Identify other Big Data resources.

INTRODUCTION

This chapter examines accounting tools that can be used for Big Data analysis. The reader may be familiar with some of the tools but may not have considered the use of the tools as a resource for analyzing Big Data. One of these tools is very helpful in the analysis of generating sales and referrals. We’ll start our discussion by examining the use of Big Data in a real-life example, using data pulled from a nationwide retailer. The example will illustrate how to access, dissect, and evaluate Big Data, both in terms of data contained in the information as well as inferences that can be drawn from the Big Data.

ACTUAL EXAMPLE OF BIG DATA

In this section, the participant is going to be involved in a real-life Big Data example. As you look at the example, keep in mind the following:

•     Notice the "look" of real Big Data.

•     Determine if any trends can be identified within the Big Data.

•     Speculate on how the trends changed.

•     Determine what management actions could be taken in view of the data.

EXAMPLE OF ACCESSING ACTUAL CORPORATE DATA—BEST BUY

Best Buy allows the public to access some of its Big Data. You can access the data by visiting https://developer.bestbuy.com/gallery.

It is necessary to get an API key, so click on the upper right hand of the website where it says Get API Key. A key will be assigned to be used when accessing the applicable apps. Note the additional series of apps that can be used.

Source: Best Buy website, https://developer.bestbuy.com/gallery

The following descriptions are from the preceding Best Buy image and define what each application does.

Query Builder

Query Builder helps users get the most out of the Best Buy APIs by creating custom queries. Create a base for your own custom queries or use the Query Builder to access Best Buy API data. You can even customize your responses to better serve your purpose.

IFTTT

IFTTT helps you create powerful connections with one simple statement: "If This, Then That." IFTTT has already integrated with channels like Facebook, Evernote, LinkedIn, email and now Best Buy. With the Best Buy channel, you can create IFTTT recipes that include product price, trend and availability changes. Check out Best Buy’s sample recipes on IFTTT.

Factual

Factual’s Global Places is a definitive database of listings for more than 65 million local businesses and points of interest in 50 countries. Global Places uses the store’s API to incorporate data on more than one thousand Best Buy store locations, giving access to dependable information for developers worldwide.

Listia

Listia is a popular online marketplace that allows users to post items they no longer need to earn credits that can be redeemed for items listed by other users or new merchandise posted by Best Buy and other retailers. By partnering with Listia, Best Buy is helping customers reduce clutter, rescuing still-usable electronics from landfills and finding good homes for new tech gear.

Tracklf

TrackIf is an innovative shopping aggregator that searches the web to find exactly the products you’re looking for. Tracklf will scour its partner sites for the best bargain of the day, as well as price-drop and supply notifications.

ShopSavvy

Best Buy’s partnership with ShopSavvy allows customers to find low online prices even when shopping in store. Shoppers can scan in-store items using the ShopSavvy app to compare competitor prices, find sales, and make online purchases and more.

CitiBank

Citibank’s ThankYou Rewards allow customers to earn points by using a participating credit card or checking account. Those points can be redeemed for a wide array of products, including tablets, gaming consoles and other electronics from Best Buy. Customers can pick up their purchases at the nearest Best Buy store or have the products shipped, making it a model of convenience for shoppers in all walks of life and a fantastic discovery tool for Best Buy customers.

Jifiti

Jifiti is a clever app for anyone weary of dropping fruitless hints about that upcoming birthday or other event. A list of suggested gifts is presented to your event guests and their gift lands as a virtual gift card in your email. It’s a thoughtful gift that allows both giver and receiver flexibility in choosing their favorites.

CatalogSpree

The Best Buy Circular is just one of the hundreds of catalogs and flyers waiting for your perusal with the CatalogSpree app. Share catalogs with friends and sorts your favorites with ease.

CowBoom

The Best Buy CowBoom brand is a trusted source for new, pre-owned and refurbished consumer electronics. CowBoom uses the commerce API to place orders through Best Buy without having to leave the CowBoom site, providing consistent branding, timely order placement, and a smooth, simple user experience.

Best Buy App

The Best Buy App puts a Best Buy store in your pocket. Browse the entire catalog, read reviews, compare specs, track My Best Buy rewards points and more. You can even make purchases right from your phone for home delivery or in-store pickup.

RedLaser

The RedLaser app allows users to scan UPC and QR codes at most major retail stores and receive instant price comparison to direct you to the lowest available price, as well as any applicable coupons or special offers. You can even cut down on web browsing time by making your purchase within the application, and My Best Buy customers can even scan their cards for instant access to loyalty benefits.

FindTheBest

FindTheBest is an online research engine that provides detailed information on more than 2,000 topics, enabling people to research with confidence. FindTheBest leverages our Products API to include timely pricing and product details for Best Buy products.

After the author had received his key to access the data (via email), he returned to the gallery page referenced previously and clicked on Query Builder.

The following image depicts the process to access the Best Buy catalog.

Source: Best Buy website, http://bestbuyapis.github.io/bby-query-builder/#/productSearch

Note that there are a number of options that can be included in the query, such as category and attribute. (See the following images.)

The author entered the data key and ran the query for the most viewed products. The following image shows the query detail.

KNOWLEDGE CHECK

1.     Query builder allows a user to do what?

a.     Perform "what if’ analysis.

b.     Dispose of electronic items they no longer need

c.     To write custom queries for Best Buy products.

d.     Software to create, "If this, then that" statements for data analysis.

2.     Which field was not available in the Best Buy attributes?

a.     Sales price.

b.     Regular price.

c.     Discount.

d.     Percent savings.

3.     To allow the Best Buy query to run, what must a user do?

a.     Have access to data mining software.

b.     Obtain an API Key.

c.     Be able to read HTML.

d.     Obtain Best Buy field translator program.

EXERCISE

The following pages are meant to be included in the following format. It is difficult to read unless you have a background in IT, or you have a program that can automatically decipher the image. Therefore, the reader should spend several minutes alone or with a partner to digest the information. What do you notice in the details?

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products."},"images":{"standard":"http://img.bbystatic.com/BestBuy_US/images/products/4854/4854

433_sc.jpg"},"links":{"product":"http://api.remix.bestbuy.com/v1/products/4854433.json?apiKey=56f

gbf8desj1h7af8dfghjk6","web":"http://www.bestbuy.com/site/apple-apple-tv-

black/4854433.p?id=1218552476525&skuId=4854433&cmp=RMX&ky=28eiIkWRnU6kpSRaThWcSId

BYJmvGGbrI","addToCart":"http://www.bestbuy.com/site/olspage.jsp?id=pcmcat152200050035&type

=category&cmp=RMX&ky=28eiIkWRnU6kpSRaThWcSIdBYJmvGGbrI&qvsids=4854433"},"names":

{"title":"Apple^® - Apple TV^® -

Black"},"prices":{"current":69.99,"regular":69.99},"rank":2,"sku":"4854433"},{"customerReviews":{"ave rageScore":"4.4","count":475},"descriptions":{"short":"Tracks steps taken, distance traveled, calories burned, stairs climbed, elapsed time and sleep metrics; wrist-based heart rate monitoring; call notifications; backlit

display"},"images":{"standard":"http://img.bbystatic.com/BestBuy_US/images/products/8681/868153
3_sc.jpg"},"links":{"product":"http://api.remix.bestbuy.com/v1/products/8681533.json?apiKey=56fgbf
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black/8681533.p?id=1219357512977&skuId=8681533&cmp=RMX&ky=28eiIkWRnU6kpSRaThWcSId

BYJmvGGbrr’,’’addToCart’’:’’http://www.bestbuy.com/site/olspage.jsp?id=pcmcat152200050035&type
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{"title":"Fitbit - Charge HR Heart Rate and Activity Tracker + Sleep Wristband (Small) -

Black^M},^Mprices^M:{^Mcurrent^M:149.99,^Mregular^M:149.99},^Mrank^M:7,^Msku":^M8681533^M},{^McustomerReviews^M:{^Ma

verageScore^M:^M4.1^M,^Mcount^M:75},’’descriptions’’:{’’short’’:’’Windows 8.1Technical details: AMD A8-Series

processor; 15.6’’ display; 6GB memory; 500GB hard driveSpecial features: Bluetooth; HDMI

output^M},^Mimages^M:{^Mstandard^M:^Mhttp://img.bbystatic.com/BestBuy_US/images/products/2996/299602
6_sc.)pg^M},^Mlinks^M:{^Mproduct^M:^Mhttp://api.remix.bestbuy.com/v1/products/2996026.)son?apiKey=56fgbf
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silver/4968016.p?id=1219645631904&skuId=4968016&cmp=RMX&ky=28eiIkWRnU6kpSRaThWcSId BYJmvGGbrI^M,^MaddToCart^M:^Mhttp://www.bestbuy.com/site/olspage.)sp?id=pcmcat152200050035&type =category&cmp=RMX&ky=28eiIkWRnU6kpSRaThWcSIdBYJmvGGbrI&qvsids=4968016^M},^Mnames^M: {^Mtitle^M:^MMicrosoft - Surface 3 - 10.8’’ - Intel Atom - 128GB -

Silver^M},^Mprices^M:{^Mcurrent^M:599.99,^Mregular^M:599.99},^Mrank^M:3,^Msku^M:^M4968016^M},{^McustomerReviews^M:{^Ma verageScore^M:null,^Mcount^M:null},^Mdescriptions^M:{^Mshort^M:^M10.8^M LCD touch screen with 1920 x 1280 resolutionWindows 8.1 operating system64GB storage capacityQuad-core processorWi-FiBluetooth interface^M},^Mimages^M:{^Mstandard^M:^Mhttp://img.bbystatic.com/BestBuy_US/images/products/4967/49670 17_sc.)pg^M},^Mlinks^M:{^Mproduct^M:^Mhttp://api.remix.bestbuy.com/v1/products/4967017.)son?apiKey=56fg bf8des)1h7af8dfgh)k6^M,^Mweb^M:^Mhttp://www.bestbuy.com/site/microsoft-surface-3-10-8-intel-atom-64gb- silver/4967017.p?id=1219645630549&skuId=4967017&cmp=RMX&ky=28eiIkWRnU6kpSRaThWcSId BYJmvGGbrI^M,^MaddToCart^M:^Mhttp://www.bestbuy.com/site/olspage.)sp?id=pcmcat152200050035&type =category&cmp=RMX&ky=28eiIkWRnU6kpSRaThWcSIdBYJmvGGbrI&qvsids=4967017^M},^Mnames^M: {^Mtitle^M:^MMicrosoft - Surface 3 - 10.8’’ - Intel Atom - 64GB -

Silver^M},^Mprices^M:{^Mcurrent^M:499.99,^Mregular^M:499.99},^Mrank^M:1,^Msku^M:^M4967017^M},{^McustomerReviews^M:{^Ma verageScore^M:^M4.6^M,^Mcount^M:2081},^Mdescriptions^M:{^Mshort^M:^M12^M touch screen with 2160 x 1440 resolutionWindows 8.1 Pro operating system128GB storage capacity4th generation Intel® Core™ i5 ProcessorMulti-position

Kickstand^M},^Mimages^M:{^Mstandard^M:^Mhttp://img.bbystatic.com/BestBuy_US/images/products/6243/624 3045_sc.)pg^M},^Mlinks^M:{^Mproduct^M:^Mhttp://api.remix.bestbuy.com/v1/products/6243045.)son?apiKey=56 fgbf8des)1h7af8dfgh)k6^M,^Mweb^M:^Mhttp://www.bestbuy.com/site/microsoft-surface-pro-3-12-intel-core-i5- 128gb-

silver/6243045.p?id=1219198824874&skuId=6243045&cmp=RMX&ky=28eiIkWRnU6kpSRaThWcSId BYJmvGGbrI^M,^MaddToCart^M:^Mhttp://www.bestbuy.com/site/olspage.)sp?id=pcmcat152200050035&type =category&cmp=RMX&ky=28eiIkWRnU6kpSRaThWcSIdBYJmvGGbrI&qvsids=6243045^M},^Mnames^M: {’’title’V’Microsoft - Surface Pro 3 - 12’ - Intel Core i5 - 128GB -

Silver"},"prices":{"current":999.99,"regular":999.99},"rank":8,"sku":"6243045"},{"customerReviews":{"a verageScore":"4.0","count":805},"descriptions":{"short":"Compatible with off-air HDTV broadcasts; retractable VHF dipoles; UHF

loop"},"images":{"standard":"http://img.bbystatic.com/BestBuy_US/images/products/8280/8280834_

sc.jpg"},"links":{"product":"http://api.remix.bestbuy.com/v1/products/8280834.json?apiKey=56fgbf8d

esj1h7af8dfghjk6","web":"http://www.bestbuy.com/site/rca-indoor-off-air-hdtv-

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IdBYJmvGGbrI","addToCart":"http://www.bestbuy.com/site/olspage.jsp?id=pcmcat152200050035&ty

pe=category&cmp=RMX&ky=28eiIkWRnU6kpSRaThWcSIdBYJmvGGbrI&qvsids=8280834"},"names

":{"title":"RCA - Indoor Off-Air HDTV

Antenna"},"prices":{"current":3.99,"regular":9.99},"rank":4,"sku":"8280834"},{"customerReviews":{"av erageScore":"4.6","count":1466},"descriptions":{"short":"1080p resolutionClear Motion Rate 120Smart TVENERGY STAR

Certified"},"images":{"standard":"http://img.bbystatic.com/BestBuy_US/images/products/5674/56740 02_sc.jpg"},"links":{"product":"http://api.remix.bestbuy.com/v1/products/5674002.json?apiKey=56fg bf8desj1h7af8dfghjk6","web":"http://www.bestbuy.com/site/samsung-40-class-40-diag–led-1080p- smart-hdtv-

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Certified"},"images":{"standard":"http://img.bbystatic.com/BestBuy_US/images/products/6594/65941 18_sc.jpg"},"links":{"product":"http://api.remix.bestbuy.com/v1/products/6594118.json?apiKey=56fg bf8desj1h7af8dfghjk6","web":"http://www.bestbuy.com/site/samsung-60-class-60-diag–led-1080p- smart-hdtv-

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Black"},"prices":{"current":849.99,"regular":1199.99},"rank":9,"sku":"6594118"},{"customerReviews":{" averageScore":null,"count":null},"descriptions":{"short":"DLP480p3D not enabled100 lumens white brightness, 100 lumens color brightnessSpeakers

included"},"images":{"standard":"http://img.bbystatic.com/BestBuy_US/images/products/5036/50360

11_sc.jpg"},"links":{"product":"http://api.remix.bestbuy.com/v1/products/5036011.json?apiKey=56fg

bf8desj1h7af8dfghjk6","web":"http://www.bestbuy.com/site/zte-spro-dlp-wireless-smart-projector-

black/5036011.p?id=1219645630545&skuId=5036011&cmp=RMX&ky=28eiIkWRnU6kpSRaThWcSId

BYJmvGGbrI","addToCart":"http://www.bestbuy.com/site/olspage.jsp?id=pcmcat152200050035&type

=category&cmp=RMX&ky=28eiIkWRnU6kpSRaThWcSIdBYJmvGGbrI&qvsids=5036011"},"names":

{"title":"ZTE - SPro DLP Wireless Smart Projector -

Black"},"prices":{"current":399.99,"regular":449.99},"rank":5,"sku":"5036011"}]}

This exercise was included to display the type of information that is being gathered in structured terms that we do not typically access. Here is where it gets interesting. The preceding data are from May 5, 2015. The data were captured and brought into Excel. The data were parsed and the desired information was extracted to make it more user-friendly. Then, the same report was run two days later (May 7) and put into the same Excel worksheet. The following images represent one large image—the far most left and far most right of the data.)

Contrast May 5 with May 7. What can you find that is particularly interesting?

What have we learned from this search?

•     The top 10 products.

•     How the products are ranked.

•     What the current price is.

•     The original sales price.

•     This report can be evaluated over different sales periods.

What uses can we make of this data?

•     It can be compared to what consumers are searching for in other stores.

•     It can be evaluated at different times (pre-and post-holiday.)

•     It can be used to identify immediate price changes.

•     It can also be used to show immediate product interest changes with the consumer.

•     It can be related to actual sales in the future (predictive).

•     It can be related to flyers sent out.

•     It can be related to product positioning on the website.

•     It can be related to special offers on the website.

•     It is especially interesting to note the uptick in gift cards and the laundry appliance. There was no indication on May 5 that either the gift cards or laundry appliance were a top-viewed product. However, on May 7 both of these items moved into the top categories. Is it possible that this information reflects potential gifts for Mother’s Day? (Note: When obtaining the permission to include the Best Buy data, the author discussed this insight with the Best Buy representative. The author was leading up to this point when the Best Buy representative said "Mother’s Day.")

There are many other conclusions and inferences that can be made from the data; however, it should be apparent that insights are possible from data that was previously untracked. It would be intriguing to see the actual sales results over the next couple of weeks and see if there is a correlation between the top products viewed to the actual sales made. Also, consider this information from the perspective of a competitor. The competitor does not even need to send in a "mystery shopper." The data are available for comparative purposes.

OPTIMIZATION

One-size pricing rarely, if ever, fits all customers. There are many different determinants of pricing, which include the following:

•     Commodity versus non-commodity status

•     Availability of product

•     Substitute products available

•     Volumes purchased

•     Seasonality

•     Related products purchased

•     Special discounts

•     Customization required

•     Lead time

•     Expiration of product

•     Quality of product

•     Brand perception

•     Competitor’s pricing tactics

•     Government laws

•     Raw material price changes

•     Other cost changes that must be passed on through pricing of product

•     Version of product

•     Where and how the product is sold (discount retailer versus high-end boutique)

Regardless of the characteristics, the seller must be aware of how these items interact and what the effect of product pricing is. If the product pricing is too high, margins may be obtained; but overall volume may decrease to the point that total revenue and profitability suffers. If the product pricing is too low, margins may suffer; but overall volume may increase to the point that total revenue and profitability may improve. Each of the characteristics can also affect the other features. For example, a customer that desires a prestigious product will expect a high price to limit the number of customers. If everyone can purchase the product, some customers will not see it as prestigious and, therefore, will not buy. The art in price setting, therefore, is to select the pricing methodology that complements the desired strategy to sell the product.

CRUISE LINE USES BIG DATA TO OPTIMIZE PRICES¹

If characteristics are understood, how can Big Data complement the price setting process to optimize an organization’s revenue? Let us examine how Carnival Cruise Lines made this happen.

Carnival Cruises wanted to segment its customer base to understand its spending patterns better. Carnival’s goals were to learn the following:

•     How to attract new customers

•     How to re-price tickets to fill more staterooms

•     Understanding customer’s spending habits on souvenirs, excursions, and extras.

To glean this information, Carnival implemented a pioneering process. The company decided to employ data scientists to analyze data, economic trends, and social trends from past customers and vacationers in general. One objective was to match clients with the most appropriate cruise ship in its fleet of 100 ships—nine brands from budget family to luxury cruises. Differentiation of customers in terms of services and related price ranges could be significant.

Because the overall profitability of the cruise is dependent on the entire cruise, the company must be able to monitor and adjust strategies that can have a daily impact. Prices may not change dynamically, but the daily results may alter strategies and promotions.

The primary metric in the cruise business is available passenger cruise days (the number of days customers are aboard ship.) According to the CEO, the total available days over the fleet is 80 million in a year. In simple terms, if every passenger spent $1 more per day during his or her trip, Carnival would add $80 million in revenue over the course of one year.

The data science team at Carnival works daily, analyzing data such as passenger behavior, vacation trends, and questions from travel agents and queries from customers. The analysis runs overnight and develops thousands of recommendations for changes to ticket prices around the world. As an example, based on projected demand, the company can change the number of reservations allocated for different ports. In addition, this analysis may also result in shifting ship capacity from one country to another country across the ocean.

Carnival understands that analytics does not mean that they are making the correct decision—only a better-informed decision. Management still relies on their human experience in addition to analytics.

Is Carnival’s approach working? The company’s performance would suggest it is. Carnival reported record earnings in the third quarter of 2015 and is planning to add more ships to its fleet in 2016.

KNOWLEDGE CHECK

4.     Carnival Cruises stresses that use of analytics to affect pricing will do what?

a.     Ensure that the best decision is made.

b.     Result in the highest possible price to be charged.

c.     Guarantee a better-informed decision.

d.     Guarantee that all options will be evaluated.

PREDICTIVE TOOLS

There are many tools that can be used to predict future outcomes. For example, what would be the advantage if we could predict the following?

1.     The probability that a customer will refer other prospects.

2.     The probability that a client will buy other products.

3.     The likelihood of an employee to refer other prospective employees.

4.     The likelihood of an employee to leave.

Basically, each of these questions would be possible to assess with data that we already have or could easily obtain. For instance, we could assess the likelihood in items 1. and 2. through customer surveys. We could assess items 3. and 4. by employee surveys or possibly even by employee email.

First, consider a tool that can be a predictor of corporate growth. The data that are used to predict this information may already be in the company system, or the data may exist in written (survey form) or may be determined by another type of feedback such as a customer follow-up call. This tool is known as the Net Promoter Score (NSP).

Frederick Reichheld of Bain Consulting developed the NSP in 2003. The simplicity of the NSP approach, as opposed to traditional customer surveys, originated with Enterprise Rental Car customer survey of two questions. Reichheld’s research shows that there is a strong correlation between a company’s growth rate and the percentage of customers who are "promoters."

KNOWLEDGE CHECK

5.     Who created the Net Promoter Score?

a.     Lencione.

b.     Reichheld.

c.     Collins.

d.     Champy.

ENTERPRISE PREDICTIVE ANALYTIC TOOLS—2014²

There are a variety of software tools to generate predictive analytics. This section is not intended as a recommendation but only offers examples of some big names and basic comments.

Revolution Analytics: www.revolutionanalytics.com/

IBM Predictive Analytics: www-01 .ibm.com/software/analytics/spss/

Actian: www.actian.com

FICO: www.fico.com/en/solutions/big-data-analytics-decision-application-development-management/

SAS: www.sas.com/en_us/software/analytics.html

Angoss: www.angoss.com

KNIME: https://www.knime.org/

RapidMiner: http://rapidminder.com

Alpine Data Labs: http://alpinenow.com/

Salford Systems: https://www.salford-systems.com/

SAP InfiniteInsight: http://go.sap.com/product/analytics/predictive-analytics.html

Blue Yonder: www.blue-yonder.com/en/

Dotplot: www.dotplot.com

Oracle: www.oracle.com/us/products/database/options/advanced-analytics/overview/index.html

BigML: http://bigml.com

STATISTICA: www.statsoft.com/

OTHER SIMPLE TOOLS TO ACCESS BIG DATA SOURCES

Attendees of the AICPA’s Controllers Annual Update received G17, which is an excellent source of data that supports the Industrial Production Statistics. It is issued monthly by the Federal Reserve. The following image represents the actual monthly production statistics by year for the overall index. The web reference is www.federalreserve.gov/RELEASES/g17/ipdisk/alltables.txt

This information can be used to determine business cycles for your industry and others, which should also dictate your management tactics. It can also be used to compare your company sales with industry trends. If your sales trends do nothing more than mirror the industry trends, then your sales staff is average. If your sales trends exceed the industry, then your sales staff is above average; and if your sales trends are lower than the industry trends, then your sales staff is below average.

So, how could Big Data have been used by the newspaper industry to identify its downward (and continuing downward) trend quickly? This information should have persuaded management teams to restructure, diversify, or abandon the newspaper industry years ago. The next analysis was performed using the IPS data for newspaper publishers and copied into Excel. Then, a chart was created to look at the industry as a whole.

Note the peak around 1986—87. This was the timeframe when personal computers became more prevalent. The trend for users to start accessing news information online was just over the horizon.

How can we use this information to understand business cycles and trends in sales revenue? The Excel data were used to create 3- and 12-month averages.

Charting out the IPS, 3- and 12-month averages produce the following graph. Note the continuous decline which is almost always below the 12-month average. The newspapers have continued their decline since the beginning of the 21^st century.

Graph the trailing averages. It is easy to see when the data fall below 1.0. Any time the data are below 1.0, the industry is declining. A prudent management team should be taking recessionary steps. When the data climb above 1.0, the industry is growing, and the management team should be concerned with expansionary actions. Unfortunately, reviewing the data with the calculations and reviewing the preceding charts, it is clear that the newspaper industry has been in continuous decline.

KNOWLEDGE CHECK

6.     Where do the Industrial Production Statistics come from?

a.     The U.S. Census.

b.     The Bureau of Labor and Statistics.

c.     The Federal Reserve.

d.     U.S. Small Business Administration.

7.     What was the industry code for newspaper publishers?

a.     51111.

b.     50001.

c.     54111.

d.     44111.

Census Data

What are some other sources of Big Data to consider using for an organization?

The U.S. Census prepares the estimate of Monthly Retail Sales from 1992 through the present. The website is www.census.gov/retail/index.html

Following is an example of the data provided by the U.S. Census. The spreadsheet contains monthly data back to 1992 and also associates the industry with the North American Industry Classification System code. It would be possible to connect this data to the IPS data from the previous example.

DATABASE TOOLS

Your data or analysis will be limited if you do not access good prediction software. To complement your spreadsheet analysis, consider acquiring Crystal Ball (www.oracle.com/technetwork/middleware/crystalball/overview/index.html) or @ Risk (www.palisade.com/risk/), which are Excel add-ins that perform Monte Carlo simulation analysis. In addition, Domo (www.domo.com) is a new business management platform that brings all business platforms together combining B.I., predictive analytics and Big Data.

The first add-in, @RISK (pronounced "at risk,") performs risk analysis using a Monte Carlo simulation to show many possible outcomes in the spreadsheet model—and tells how likely they are to occur. It mathematically and objectively computes and tracks many different possible future scenarios, then identifies the probabilities and risks associated with each different scenario. This means users can judge which risks to take and which ones to avoid, allowing for the best decision making under uncertainty.

@RISK also helps plan the best risk management strategies through the integration of RISKOptimizer, which combines Monte Carlo simulation with the latest solving technology to optimize any spreadsheet with uncertain values. Using genetic algorithms³ or OptQuest, along with @RISK functions, RISKOptimizer can determine the best allocation of resources, the optimal asset allocation, the most efficient schedule, and much more.⁴

Oracle Crystal Ball is the leading spreadsheet-based application for predictive modeling, forecasting, simulation, and optimization. It gives unparalleled insight into the critical factors affecting risk. With Crystal Ball, users make the right tactical decisions to reach the objectives and gain a competitive edge under even the most uncertain market conditions.⁵

According to Domo’s website, "To do the job well, users need the right information at the right time. Unfortunately, that information lives in an ever-increasing mess of disconnected spreadsheets, systems, databases, and applications."⁶

Domo solves that problem by bringing a business and its data together in one intuitive platform. With Domo, users can create dashboards to put all of their information in one place and use it to make faster, better-informed decisions.

KNOWLEDGE CHECK

8.     The monthly retail sales data can be obtained from

a.     The U.S. Census.

b.     Bureau of Labor and Statistics.

c.     The Federal Reserve.

d.     U.S. Small Business Administration.

BIG DATA VISUALIZATION

What is Big Data visualization? According to SAS:⁷

Data visualization is the presentation of data in a pictorial or graphical format. For centuries, people have depended on visual representations such as charts and maps to understand information more easily and quickly.

As more and more data are collected and analyzed, decision makers at all levels welcome data visualization software that enables them to see analytical results presented visually, find relevance among the millions of variables, communicate concepts and hypotheses to others, and even predict the future.

Because of the way the human brain processes information, it is faster for people to grasp the meaning of many data points when they are displayed in charts and graphs rather than poring over piles of spreadsheets or reading pages and pages of reports.

Text Analytics⁸

Text analytics is the process of deriving high-quality information from text. Insights are derived from understanding patterns and trends through statistical pattern learning. Text mining requires structuring the input text, identifying patterns within the structured data, and finally interpreting the output. Text mining includes text categorization, text clustering, concept or entity extraction, production of granular taxonomies, sentiment analysis, document summarization, and entity relation modeling (that is, learning relations between named entities). The goal of text mining is to transform text into data by use of natural language processing and analytical methods. One example is to scan a set of documents written in a natural language for predictive classification purposes or populate a database with the extracted information.

•     Named entities extraction: Helps answer the questions: "who, what, and where?"

•     Document summarization: The creation of a shortened version of a text by a computer program.

•     Theme extraction: Answers the question: "What are the important words being used?"

•     Concept extraction: Answers the question: "What are the important high-level concepts?"

•     Sentiment analysis: Answers the question: "Is what’s being said ’positive’ or ’negative’?"

Practice Questions

1.     List some of the determinants of pricing.

2.     Describe the Big Data accessed from Best Buy.

3.     List several sources of Big Data that can be compared to your organization.

4.     Describe what text analytics is.